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Accessing ALBP information directly to guide the search process is necessary because retrieving them from the ecole.scip.Model is pretty inconvenient. The assumption of having all the problem information available is largely accepted in the literature and is a basic assumption in all papers.
Inherit from FileGenerator class
The ecole.instance.FileGenerator iterates over a folder and its subfolders to find .mps and .lp files.
The class is written in C++ and could be used to read row ALBP files, retrieve the information, and create a scip.Model which stores ALBP information directly.
A list of possible issues is the following:
Each problem presents a different dataset structure and a switch statement would be required to differentiate the procedure for all of them.
Python objects and .lp model
pyscipopt.Model objects are not serializable, therefore it is impossible to rely on these only.
Problem data are stored as plain Python dictionaries using pickle. The instance generator iterates over .lp problem files, reads the model, initializes a pyscipopt.Model, reads model data, and appends this to the data attribute of the pyscipopt.Model object.
Randomization of results
The ecole.RandomGenerator class controls the fetching process.
The text was updated successfully, but these errors were encountered:
ALBP file reader
Accessing ALBP information directly to guide the search process is necessary because retrieving them from the
ecole.scip.Model
is pretty inconvenient. The assumption of having all the problem information available is largely accepted in the literature and is a basic assumption in all papers.Inherit from FileGenerator class
The
ecole.instance.FileGenerator
iterates over a folder and its subfolders to find.mps
and.lp
files.The class is written in C++ and could be used to read row ALBP files, retrieve the information, and create a
scip.Model
which stores ALBP information directly.A list of possible issues is the following:
Python objects and
.lp
modelpyscipopt.Model
objects are not serializable, therefore it is impossible to rely on these only.Problem data are stored as plain Python dictionaries using pickle. The instance generator iterates over
.lp
problem files, reads the model, initializes apyscipopt.Model
, reads model data, and appends this to thedata
attribute of thepyscipopt.Model
object.Randomization of results
The
ecole.RandomGenerator
class controls the fetching process.The text was updated successfully, but these errors were encountered: